Related papers: In Defense of the Paper
In recent years, machine learning has transitioned from a field of academic research interest to a field capable of solving real-world business problems. However, the deployment of machine learning models in production systems can present a…
Meta-learning researchers face two fundamental issues in their empirical work: prototyping and reproducibility. Researchers are prone to make mistakes when prototyping new algorithms and tasks because modern meta-learning methods rely on…
The current flood of information in all areas of machine learning research, from computer vision to reinforcement learning, has made it difficult to make aggregate scientific inferences. It can be challenging to distill a myriad of similar…
Most scholarly works are distributed online in PDF format, which can present significant accessibility challenges for blind and low-vision readers. To characterize the scope of this issue, we perform a large-scale analysis of 20K open- and…
Within the past few decades we have witnessed digital revolution, which moved scholarly communication to electronic media and also resulted in a substantial increase in its volume. Nowadays keeping track with the latest scientific…
The peer review system as used in several computer science communities has several flaws including long review times, overloaded reviewers, as well as fostering of niche topics. These flaws decrease quality, lower impact, slowdown the…
Machine Learning requires large amounts of labeled data to fit a model. Many datasets are already publicly available, nevertheless forcing application possibilities of machine learning to the domains of those public datasets. The…
The automated categorization (or classification) of texts into predefined categories has witnessed a booming interest in the last ten years, due to the increased availability of documents in digital form and the ensuing need to organize…
Peer review is a widely accepted mechanism for research evaluation, playing a pivotal role in academic publishing. However, criticisms have long been leveled at this mechanism, mostly because of its poor efficiency and low reproducibility.…
The number of scientific publications is constantly rising, increasing the strain on the review process. The number of submissions is actually higher, as each manuscript is often reviewed several times before publication. To face the deluge…
Science depends on a communication system, and today that is largely provided by digital technologies such as the internet and web. Despite that digital technologies provide the infrastructure for that communication system, peer-reviewed…
In computer science, conferences and journals conduct peer review in order to decide what to publish. Many have pointed out the inherent weaknesses in peer review, including those of bias, quality, and accountability. Many have suggested…
There has been increasing concern within the machine learning community that we are in a reproducibility crisis. As many have begun to work on this problem, all work we are aware of treat the issue of reproducibility as an intrinsic binary…
Research is facing a reproducibility crisis, in which the results and findings of many studies are difficult or even impossible to reproduce. This is also the case in machine learning (ML) and artificial intelligence (AI) research. Often,…
Machine reading comprehension is a challenging task and hot topic in natural language processing. Its goal is to develop systems to answer the questions regarding a given context. In this paper, we present a comprehensive survey on…
Large language models offer a tempting solution to address the peer review crisis. This position paper argues that today's AI systems should not be used to produce paper reviews. We ground this position in an empirical comparison of human-…
Review articles summarize state-of-the-art work and provide a means to organize the growing number of scholarly publications. However, the current review method and publication mechanisms hinder the impact review articles can potentially…
The field of scientific publishing that is served by LaTeX is increasingly dependent on the availability of metadata about publications. We discuss how to use LaTeX classes and BibTeX styles to curate metadata throughout the life cycle of a…
Machine Learning software documentation is different from most of the documentations that were studied in software engineering research. Often, the users of these documentations are not software experts. The increasing interest in using…
Scientific publishing is in a transition between the old paper-bound, static forms and the new electronic media with its interactive, dynamic possibilities. This takes place in the context of imploding library budgets and exploding magazine…